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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

        This report was generated using MultiQC, version 1.22.3

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        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2024-07-29, 18:51 CEST based on data in: /Volumes/mrna/Resultados/fastqc


        General Statistics

        Showing 310/310 rows and 3/6 columns.
        Sample Name% Dups% GCM Seqs
        L_284_1
        84.0%
        48%
        42.7M
        L_284_2
        84.5%
        49%
        42.7M
        L_286_1
        75.0%
        48%
        37.2M
        L_286_2
        75.4%
        49%
        37.2M
        L_287_1
        95.8%
        50%
        22.4M
        L_287_2
        96.1%
        51%
        22.4M
        L_288_1
        88.7%
        49%
        30.1M
        L_288_2
        89.1%
        50%
        30.1M
        L_290_1
        92.8%
        47%
        21.6M
        L_290_2
        92.6%
        48%
        21.6M
        L_293_1
        75.5%
        48%
        31.4M
        L_293_2
        75.6%
        48%
        31.4M
        L_294_1
        76.6%
        48%
        23.7M
        L_294_2
        76.0%
        49%
        23.7M
        L_296_1
        76.3%
        48%
        31.0M
        L_296_2
        76.4%
        49%
        31.0M
        L_298_1
        82.9%
        47%
        34.2M
        L_298_2
        83.3%
        48%
        34.2M
        L_299_1
        76.7%
        48%
        23.3M
        L_299_2
        76.7%
        48%
        23.3M
        L_300_1
        73.5%
        48%
        21.5M
        L_300_2
        73.4%
        49%
        21.5M
        L_301_1
        77.1%
        48%
        35.8M
        L_301_2
        77.2%
        48%
        35.8M
        L_303_1
        94.0%
        49%
        32.1M
        L_303_2
        94.4%
        49%
        32.1M
        L_307_1
        93.6%
        49%
        39.4M
        L_307_2
        94.0%
        50%
        39.4M
        L_309_1
        80.3%
        49%
        21.7M
        L_309_2
        79.9%
        50%
        21.7M
        L_312_1
        81.8%
        47%
        15.6M
        L_312_2
        82.3%
        47%
        15.6M
        L_313_1
        79.4%
        48%
        22.5M
        L_313_2
        79.0%
        49%
        22.5M
        L_314_1
        93.4%
        49%
        31.3M
        L_314_2
        93.2%
        50%
        31.3M
        L_315_1
        94.8%
        47%
        30.6M
        L_315_2
        94.7%
        48%
        30.6M
        L_318_1
        93.8%
        49%
        23.9M
        L_318_2
        95.4%
        50%
        23.9M
        L_319_1
        83.4%
        49%
        21.2M
        L_319_2
        85.7%
        50%
        21.2M
        L_321_1
        81.8%
        49%
        21.3M
        L_321_2
        83.1%
        50%
        21.3M
        L_325_1
        85.9%
        49%
        22.2M
        L_325_2
        87.8%
        49%
        22.2M
        L_330_1
        81.1%
        48%
        22.0M
        L_330_2
        82.6%
        49%
        22.0M
        L_331_1
        82.5%
        49%
        24.8M
        L_331_2
        84.5%
        50%
        24.8M
        L_334_1
        90.7%
        47%
        23.4M
        L_334_2
        92.5%
        48%
        23.4M
        L_337_1
        71.6%
        49%
        24.9M
        L_337_2
        72.7%
        50%
        24.9M
        L_340_1
        84.4%
        49%
        21.2M
        L_340_2
        86.2%
        49%
        21.2M
        L_343_1
        72.2%
        50%
        20.2M
        L_343_2
        72.2%
        51%
        20.2M
        L_344_1
        87.6%
        48%
        20.6M
        L_344_2
        87.7%
        49%
        20.6M
        L_345_1
        84.7%
        50%
        24.6M
        L_345_2
        84.9%
        50%
        24.6M
        L_346_1
        86.7%
        48%
        20.8M
        L_346_2
        86.5%
        48%
        20.8M
        L_350_1
        83.8%
        49%
        20.7M
        L_350_2
        83.8%
        49%
        20.7M
        L_359_1
        79.7%
        50%
        26.6M
        L_359_2
        79.8%
        50%
        26.6M
        L_360_1
        88.0%
        48%
        20.1M
        L_360_2
        88.1%
        49%
        20.1M
        L_363_1
        79.0%
        49%
        19.1M
        L_363_2
        79.1%
        49%
        19.1M
        L_366_1
        93.0%
        50%
        25.6M
        L_366_2
        93.0%
        51%
        25.6M
        L_371_1
        90.7%
        50%
        19.6M
        L_371_2
        90.6%
        51%
        19.6M
        L_372_1
        88.8%
        49%
        24.8M
        L_372_2
        89.1%
        50%
        24.8M
        L_373_1
        90.1%
        49%
        26.5M
        L_373_2
        90.1%
        50%
        26.5M
        L_375_1
        95.3%
        54%
        23.1M
        L_375_2
        95.2%
        54%
        23.1M
        L_380_1
        89.0%
        49%
        24.7M
        L_380_2
        88.7%
        50%
        24.7M
        L_387_1
        82.7%
        49%
        26.6M
        L_387_2
        82.7%
        50%
        26.6M
        L_390_1
        85.1%
        49%
        30.2M
        L_390_2
        85.0%
        49%
        30.2M
        L_394_1
        85.2%
        50%
        26.7M
        L_394_2
        85.1%
        50%
        26.7M
        L_398_1
        84.3%
        49%
        19.5M
        L_398_2
        84.3%
        49%
        19.5M
        L_400_1
        84.3%
        49%
        23.8M
        L_400_2
        84.8%
        50%
        23.8M
        L_403_1
        89.7%
        50%
        25.7M
        L_403_2
        89.9%
        50%
        25.7M
        L_408_1
        91.6%
        49%
        26.2M
        L_408_2
        91.7%
        50%
        26.2M
        L_409_1
        80.8%
        49%
        25.3M
        L_409_2
        80.8%
        50%
        25.3M
        L_410_1
        90.3%
        46%
        17.8M
        L_410_2
        90.7%
        46%
        17.8M
        L_413_1
        88.3%
        49%
        24.6M
        L_413_2
        88.5%
        50%
        24.6M
        L_414_1
        75.8%
        49%
        22.0M
        L_414_2
        76.2%
        49%
        22.0M
        L_417_1
        80.1%
        49%
        24.2M
        L_417_2
        81.6%
        49%
        24.2M
        L_421_1
        81.7%
        48%
        19.0M
        L_421_2
        81.8%
        49%
        19.0M
        L_428_1
        86.4%
        49%
        31.0M
        L_428_2
        86.3%
        49%
        31.0M
        L_429_1
        91.1%
        48%
        17.1M
        L_429_2
        91.1%
        49%
        17.1M
        L_433_1
        87.5%
        50%
        24.6M
        L_433_2
        87.7%
        50%
        24.6M
        L_439_1
        88.8%
        49%
        23.7M
        L_439_2
        88.9%
        49%
        23.7M
        L_443_1
        82.2%
        49%
        25.7M
        L_443_2
        82.5%
        49%
        25.7M
        L_457_1
        79.1%
        49%
        15.5M
        L_457_2
        79.3%
        49%
        15.5M
        L_458_1
        87.5%
        49%
        24.7M
        L_458_2
        88.9%
        50%
        24.7M
        L_459_1
        87.3%
        49%
        24.6M
        L_459_2
        87.5%
        49%
        24.6M
        L_460_1
        87.3%
        49%
        23.6M
        L_460_2
        87.3%
        50%
        23.6M
        L_461_1
        92.3%
        49%
        24.4M
        L_461_2
        92.4%
        50%
        24.4M
        L_471_1
        90.4%
        48%
        30.6M
        L_471_2
        90.7%
        49%
        30.6M
        L_472_1
        90.9%
        48%
        33.0M
        L_472_2
        90.9%
        49%
        33.0M
        L_473_1
        87.0%
        49%
        26.5M
        L_473_2
        87.1%
        49%
        26.5M
        L_479_1
        91.8%
        49%
        21.9M
        L_479_2
        91.8%
        50%
        21.9M
        L_484_1
        89.1%
        49%
        25.7M
        L_484_2
        88.9%
        49%
        25.7M
        L_485_1
        86.7%
        49%
        28.2M
        L_485_2
        86.8%
        49%
        28.2M
        L_486_1
        89.4%
        49%
        23.0M
        L_486_2
        89.5%
        49%
        23.0M
        L_487_1
        86.4%
        49%
        24.6M
        L_487_2
        86.2%
        49%
        24.6M
        L_488_1
        77.2%
        48%
        20.8M
        L_488_2
        77.8%
        49%
        20.8M
        L_491_1
        83.8%
        49%
        24.2M
        L_491_2
        83.9%
        49%
        24.2M
        L_492_1
        83.5%
        50%
        32.3M
        L_492_2
        83.6%
        50%
        32.3M
        L_496_1
        87.4%
        49%
        35.0M
        L_496_2
        88.2%
        49%
        35.0M
        L_497_1
        88.2%
        49%
        25.6M
        L_497_2
        88.4%
        50%
        25.6M
        L_498_1
        86.9%
        48%
        25.3M
        L_498_2
        87.2%
        49%
        25.3M
        SC_284_1
        69.4%
        50%
        21.1M
        SC_284_2
        69.5%
        50%
        21.1M
        SC_286_1
        88.0%
        50%
        33.7M
        SC_286_2
        88.3%
        51%
        33.7M
        SC_287_1
        78.9%
        49%
        41.5M
        SC_287_2
        79.2%
        50%
        41.5M
        SC_288_1
        82.9%
        49%
        30.0M
        SC_288_2
        83.0%
        50%
        30.0M
        SC_290_1
        78.5%
        49%
        22.6M
        SC_290_2
        78.2%
        50%
        22.6M
        SC_292_1
        89.4%
        49%
        32.8M
        SC_292_2
        89.8%
        50%
        32.8M
        SC_293_1
        92.4%
        50%
        30.7M
        SC_293_2
        92.7%
        52%
        30.7M
        SC_294_1
        93.5%
        48%
        24.4M
        SC_294_2
        93.0%
        49%
        24.4M
        SC_296_1
        90.1%
        50%
        29.6M
        SC_296_2
        90.5%
        51%
        29.6M
        SC_298_1
        68.0%
        49%
        23.6M
        SC_298_2
        67.8%
        50%
        23.6M
        SC_299_1
        89.8%
        50%
        28.7M
        SC_299_2
        90.0%
        51%
        28.7M
        SC_300_1
        89.2%
        50%
        28.8M
        SC_300_2
        89.8%
        51%
        28.8M
        SC_301_1
        93.5%
        50%
        20.6M
        SC_301_2
        93.4%
        51%
        20.6M
        SC_303_1
        84.7%
        50%
        31.3M
        SC_303_2
        84.7%
        51%
        31.3M
        SC_307_1
        88.2%
        50%
        21.3M
        SC_307_2
        88.2%
        51%
        21.3M
        SC_309_1
        75.1%
        50%
        20.0M
        SC_309_2
        75.2%
        51%
        20.0M
        SC_312_1
        90.9%
        50%
        21.0M
        SC_312_2
        90.0%
        52%
        21.0M
        SC_313_1
        67.1%
        50%
        23.1M
        SC_313_2
        67.2%
        50%
        23.1M
        SC_314_1
        94.5%
        50%
        25.3M
        SC_314_2
        94.5%
        51%
        25.3M
        SC_315_1
        91.3%
        50%
        30.6M
        SC_315_2
        91.8%
        51%
        30.6M
        SC_318_1
        91.3%
        51%
        16.4M
        SC_318_2
        94.0%
        52%
        16.4M
        SC_319_1
        91.6%
        49%
        31.0M
        SC_319_2
        92.1%
        51%
        31.0M
        SC_321_1
        92.4%
        51%
        25.0M
        SC_321_2
        94.4%
        52%
        25.0M
        SC_325_1
        93.5%
        47%
        22.8M
        SC_325_2
        93.4%
        48%
        22.8M
        SC_330_1
        82.7%
        50%
        21.5M
        SC_330_2
        81.7%
        51%
        21.5M
        SC_331_1
        90.2%
        48%
        27.8M
        SC_331_2
        90.7%
        49%
        27.8M
        SC_334_1
        91.0%
        51%
        24.2M
        SC_334_2
        90.7%
        52%
        24.2M
        SC_337_1
        78.9%
        49%
        23.1M
        SC_337_2
        79.0%
        50%
        23.1M
        SC_340_1
        88.8%
        50%
        34.1M
        SC_340_2
        89.2%
        51%
        34.1M
        SC_343_1
        86.0%
        49%
        28.1M
        SC_343_2
        86.3%
        50%
        28.1M
        SC_344_1
        66.1%
        49%
        23.2M
        SC_344_2
        66.3%
        50%
        23.2M
        SC_345_1
        88.8%
        50%
        30.0M
        SC_345_2
        89.2%
        51%
        30.0M
        SC_346_1
        69.3%
        49%
        31.4M
        SC_346_2
        69.7%
        50%
        31.4M
        SC_350_1
        72.1%
        51%
        29.5M
        SC_350_2
        72.6%
        51%
        29.5M
        SC_359_1
        94.4%
        50%
        22.9M
        SC_359_2
        93.4%
        51%
        22.9M
        SC_360_1
        83.1%
        49%
        34.0M
        SC_360_2
        83.4%
        50%
        34.0M
        SC_363_1
        73.6%
        50%
        19.6M
        SC_363_2
        72.8%
        51%
        19.6M
        SC_366_1
        71.3%
        50%
        20.6M
        SC_366_2
        71.5%
        51%
        20.6M
        SC_371_1
        74.7%
        49%
        26.8M
        SC_371_2
        75.0%
        50%
        26.8M
        SC_372_1
        82.2%
        49%
        27.6M
        SC_372_2
        82.4%
        50%
        27.6M
        SC_373_1
        92.1%
        50%
        32.2M
        SC_373_2
        92.5%
        51%
        32.2M
        SC_375_1
        91.6%
        50%
        28.9M
        SC_375_2
        92.0%
        52%
        28.9M
        SC_380_1
        60.4%
        49%
        20.4M
        SC_380_2
        60.1%
        50%
        20.4M
        SC_387_1
        86.5%
        51%
        21.6M
        SC_387_2
        85.5%
        52%
        21.6M
        SC_390_1
        64.6%
        49%
        21.6M
        SC_390_2
        64.7%
        50%
        21.6M
        SC_394_1
        90.3%
        50%
        31.0M
        SC_394_2
        90.6%
        51%
        31.0M
        SC_398_1
        92.7%
        51%
        19.8M
        SC_398_2
        92.2%
        52%
        19.8M
        SC_400_1
        71.3%
        50%
        20.0M
        SC_400_2
        71.2%
        51%
        20.0M
        SC_403_1
        94.1%
        50%
        20.4M
        SC_403_2
        93.2%
        52%
        20.4M
        SC_409_1
        93.2%
        51%
        20.7M
        SC_409_2
        92.3%
        52%
        20.7M
        SC_410_1
        86.6%
        50%
        27.1M
        SC_410_2
        86.9%
        51%
        27.1M
        SC_413_1
        86.2%
        50%
        32.3M
        SC_413_2
        86.6%
        51%
        32.3M
        SC_414_1
        90.6%
        50%
        32.5M
        SC_414_2
        91.1%
        51%
        32.5M
        SC_417_1
        89.8%
        50%
        31.0M
        SC_417_2
        90.0%
        51%
        31.0M
        SC_421_1
        94.3%
        50%
        26.4M
        SC_421_2
        94.9%
        51%
        26.4M
        SC_428_1
        94.9%
        49%
        19.1M
        SC_428_2
        94.1%
        51%
        19.1M
        SC_429_1
        63.7%
        50%
        22.6M
        SC_429_2
        63.7%
        50%
        22.6M
        SC_433_1
        86.4%
        50%
        34.5M
        SC_433_2
        86.8%
        51%
        34.5M
        SC_439_1
        96.0%
        50%
        21.0M
        SC_439_2
        96.3%
        51%
        21.0M
        SC_443_1
        92.6%
        50%
        28.3M
        SC_443_2
        92.1%
        51%
        28.3M
        SC_457_1
        89.9%
        49%
        28.0M
        SC_457_2
        90.3%
        50%
        28.0M
        SC_459_1
        92.6%
        49%
        33.0M
        SC_459_2
        93.2%
        50%
        33.0M
        SC_460_1
        90.0%
        50%
        23.2M
        SC_460_2
        89.3%
        51%
        23.2M
        SC_461_1
        79.5%
        50%
        30.7M
        SC_461_2
        79.8%
        51%
        30.7M
        SC_471_1
        91.9%
        51%
        23.9M
        SC_471_2
        92.3%
        51%
        23.9M
        SC_472_1
        88.3%
        49%
        30.5M
        SC_472_2
        88.7%
        50%
        30.5M
        SC_484_1
        92.8%
        50%
        24.7M
        SC_484_2
        92.4%
        52%
        24.7M
        SC_485_1
        92.8%
        50%
        21.3M
        SC_485_2
        93.4%
        51%
        21.3M
        SC_486_1
        95.7%
        49%
        10.2M
        SC_486_2
        95.6%
        50%
        10.2M
        SC_487_1
        71.4%
        49%
        19.7M
        SC_487_2
        71.1%
        50%
        19.7M
        SC_488_1
        91.3%
        50%
        30.4M
        SC_488_2
        91.8%
        51%
        30.4M
        SC_491_1
        91.6%
        49%
        29.9M
        SC_491_2
        92.2%
        50%
        29.9M
        SC_492_1
        93.0%
        50%
        29.1M
        SC_492_2
        93.6%
        51%
        29.1M
        SC_496_1
        93.5%
        50%
        26.0M
        SC_496_2
        93.2%
        51%
        26.0M
        SC_497_1
        93.2%
        50%
        25.6M
        SC_497_2
        93.8%
        51%
        25.6M
        SC_498_1
        95.3%
        49%
        21.9M
        SC_498_2
        95.4%
        50%
        21.9M

        FastQC

        Version: 0.12.1

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Created with MultiQC

        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Created with MultiQC

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Created with MultiQC

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Created with MultiQC

        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Created with MultiQC

        Sequence Length Distribution

        All samples have sequences of a single length (150bp).

        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Created with MultiQC

        Overrepresented sequences by sample

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        Created with MultiQC

        Top overrepresented sequences

        Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

        Showing 20/20 rows and 3/3 columns.
        Overrepresented sequenceSamplesOccurrences% of all reads
        GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG
        109
        4500984
        0.0566%
        CTTTCCATTTTTTATTAATTGAAGCACAGAGAAAAGAGGCAAAATGATTA
        42
        1585577
        0.0200%
        CTGAGATGCTTTTAAATGTGATGTTATAAGCCTAAGGCAGCTTGACTTGC
        27
        797859
        0.0100%
        TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT
        22
        873151
        0.0110%
        GGGTGAGGTAAAATGGCTGAGTGAAGCATTGGACTGTAAATCTAAAGACA
        21
        1030890
        0.0130%
        GCCCATTTGAGTATTTTGTTTTCAATTAGGGAGATAGTTGGTATTAGGAT
        18
        654100
        0.0082%
        ATTCGGTTCAGTCTAATCCTTTTTGTAGTCACTCATAGGCCAGACTTAGG
        15
        486578
        0.0061%
        GCAAAACCCCACTCTGCATCAACTGAACGCAAATCAGCCACTTTAATTAA
        14
        646657
        0.0081%
        GTTGTCGTGCAGGTAGAGGCTTACTAGAAGTGTGAAAACGTAGGCTTGGA
        12
        409363
        0.0052%
        TGCAGGTAGAGGCTTACTAGAAGTGTGAAAACGTAGGCTTGGATTAAGGC
        12
        413820
        0.0052%
        GTGCAGGTAGAGGCTTACTAGAAGTGTGAAAACGTAGGCTTGGATTAAGG
        11
        386015
        0.0049%
        TATTAATTGAAGCACAGAGAAAAGAGGCAAAATGATTAAAGAAATTTATG
        10
        381129
        0.0048%
        CTCATCAATAGATGGAGACATACAGAAATAGTCAAACCACATCTACAAAA
        10
        334815
        0.0042%
        AAAAAACTTGTTGCTGCAAGTCAAGCTGCCTTAGGCTTATAACATCACAT
        9
        231591
        0.0029%
        GGCTGAGATGCTTTTAAATGTGATGTTATAAGCCTAAGGCAGCTTGACTT
        9
        243814
        0.0031%
        CTCTTTTGTTGCCTTGGGCTTGTGTTTCACGAGCTCAACAAGTGCAGTTT
        8
        221816
        0.0028%
        AAAAGAGGCAAAATGATTAAAGAAATTTATGTTTTTTAGACAGGGTGTTG
        7
        213864
        0.0027%
        CGCAAATCAGCCACTTTAATTAAGCTAAGCCCTTACTAGACCAATGGGAC
        7
        224940
        0.0028%
        GACAAATCAAGAAACAAACTGCACTTGTTGAGCTCGTGAAACACAAGCCC
        7
        218033
        0.0027%
        CTTGGATTAAGGCGACAGCGATTTCTAGGATAGTCAGTAGAATTAGAATT
        6
        178502
        0.0022%

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        Created with MultiQC

        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        FastQC0.12.1